Aging is characterized by wide variation in healthspan; some adults become frail in early old age while others remain fit into their 90s and beyond. In animal models, genetic mutations that slow aging also delay a diverse set of age-related diseases. Our GWAS of longevity and age-related phenotypes have identified both genome- wide significant as well as interesting suggestive associations. Many genes function in neuronal, immune, and DNA repair pathways known to be of importance to aging. However, the causal mechanisms underlying the genetic associations have not been elucidated. We propose to use a systems biology approach to extend our genetic studies of aging to examine the relationships among healthy aging phenotypes, genetic polymorphisms, gene expression, DNA methylation, and metabolic factors. Framingham Heart Study (FHS) participants are deeply phenotyped including all domains of aging and have dense genotyping, gene expression (mRNA), DNA methylation, and state-of-the-art metabolomics data providing us with the unique opportunity to extend our GWAS findings to identify multi-omic profiles associated with healthy aging phenotypes. This renewal application seeks to leverage these existing resources in FHS participants using new teams of accomplished investigators in the areas of omics. We hypothesize that using multiple-omics resources and novel integrative models will facilitate discovery of single genes and multi-gene biologic networks underpinning healthy aging phenotypes. Using cross-sectional and longitudinal healthy aging phenotypes from our parent grant (including longevity, morbidity-free survival, healthy aging index, grip strength, measures of physical and cognitive function) we propose the following specific aims: Aim 1. To identify mRNA transcripts associated with healthy aging phenotypes; Aim 2. To investigate genome-wide DNA methylation patterns in relation to healthy aging phenotypes; Aim 3. To investigate the association of metabolomic markers with healthy aging phenotypes; Aim 4. To integrate the results of the genomic and metabolomics associations in Aims 1- 3 and to identify molecular mechanisms underlying healthy aging phenotypes. Systematically integrating results across healthy aging phenotypes and Omics using network approaches will facilitate identification of key sets of genes and biologic pathways regulating aging. We will incorporate SNPs from existing GWAS and Exomechip data in the identified genes. Our established collaborations permit replication of findings in independent samples. We plan to take the most promising results on to future validation work in animal models. The knowledge gained from this proposal will elucidate important mechanistic insights into the molecular basis of aging. Ultimately the knowledge may lead to interventions to slow aging, and/or to identification of therapeutic targets to delay age-related disease so that older adults may enjoy good health.